Method and system for scheduling inbound inquiries

ABSTRACT

A method and system schedules inbound inquiries, such as inbound telephone calls, for response by agents in an order that is based in part on the forecasted outcome of the inbound inquiries. A scheduling module applies inquiry information to a model to forecast the outcome of an inbound inquiry. The forecasted outcome is used to set a priority value for ordering the inquiry. The priority value may be determined by solving a constrained optimization problem that seeks to maximize an objective function, such as maximizing an agent&#39;s productivity to produce sales or to minimize inbound call attrition. The inbound call may be placed on a virtual hold or be responded to on a real-time basis based on the inbound inquiry&#39;s priority value. A modeling module generates models that forecast inquiry outcomes based on a history and inquiry information. Statistical analysis such as regression analysis determines the model with the outcome related to the nature of the inquiry. Forecasted outcomes are based on the goal of the inbound calls and include factors such as probability an inbound caller will hang up, probability that an inbound caller will alter a business relationship based on hold time, probability that an inbound caller will make a purchase, and the relative probable reward of responding to an inbound call.

TECHNICAL FIELD

This invention relates in general to the fields of telephony andcomputer networks, and more particularly to a method and system forscheduling inbound inquires made by telephone or by other electronicmessages.

BACKGROUND OF THE INVENTION

Telephone calling centers represent the front line for customer serviceand marketing operations of many businesses. Typical calling centersreceive or make hundreds of telephone calls per day with the aid ofautomated telephony equipment. With the Internet growing in importanceas a way of communicating with customers, calling centers have alsoevolved to send and respond to electronic messages, such as e-mail orinstant messages.

Calling centers often play a dual role of both sending outboundinquiries and answering inbound inquiries. For instance, calling centersuse predictive dialers that automatically dial outbound telephone callsto contact individuals and then transfer the contacted individuals toagents when the individual answers the phone. Inbound telephone calls byindividuals to the calling center are received by telephony equipment inthe calling center and distributed to agents as the agents becomeavailable. Calling centers often combine outbound and inbound functionsas a way to improve the talk time efficiency of calling center agents.Thus, for instance, when inbound calls have expected hold times that areacceptable, agents may be reassigned to place outbound telephone callsto help ensure that the agents are fully occupied.

One important goal for calling centers that receive inbound inquiries,such as telephone calls or electronic message inquiries, is to transferthe inbound inquiries to appropriate agents as quickly and efficientlyas possible. A variety of telephone call receiving devices arecommercially available to help meet this goal. One such receiving deviceis an automatic call distribution system (“ACD”) that receives pluralinbound telephone calls and then distributes the received inbound callsto agents based on agent skill set, information available about thecaller, and rules that match inbound callers to desired queues. Inboundcalls may be routed to different queues based on rules and data,allowing a basic prioritization of inbound calls. For example, inboundcallers seeking information about a new credit card account might beassigned to a different queue than inbound callers having questionsabout their account balances. Once assigned to a queue, calls in thatqueue are generally handled in a first-in-first-out basis. Thus, acaller's hold time generally depends upon the caller's depth in thequeue.

Another type of call receiving device is a voice response unit (“VRU”),also known as an interactive voice response system. When an inbound callis received by a VRU, the caller is generally greeted with an automatedvoice that queries for information such as the caller's account number.Information provided by the caller is typically used to route the callto an appropriate queue. VRUs are used in conjunction with ACDs, butalso improve performance of less complex receiving devices such as PBXsystems.

As telephony migrates from conventional telephone signals to the use ofInternet based computer networks, voice over internet protocol (“VOIP”)will become an increasingly common platform for handling inboundtelephone calls. One advantage of VOIP is enhanced access to accountinformation for inbound calls with improved speed and accuracy. Forexample, conventional ACD and VRU systems collect caller informationwhen inbound calls are received. One example of such caller informationis automated number identification (“ANI”) information provided bytelephone networks that identify the telephone number of the inboundcall. Another example is destination number identification systeminformation (“DNIS”) which allows the purpose of the inbound call to bedetermined from the telephone number dialed by the inbound caller. Usingthis caller information and account information gathered by a VRU orACD, conventional calling centers are able to gather information on thecaller and provide that information to the agent. The use of VOIPimproves the integration of data and telephony by passing both data andtelephony through a network with internet protocol and by combiningvoice inquiries with electronic message inquiries, such as e-mail. Oneexample of such integration is the Intelligent Contact Management(“ICM”) solution sold by CISCO Systems, Inc. Another example is theintegrated response systems available from eShare Technologies,described in greater detail at www.eShare.com.

Although telephone receiving devices provide improved distribution ofinbound telephone calls to agents, the receiving devices are generallynot helpful in managing hold times when the number of inbound callsexceeds the agent answering capacity. For instance, customers tend tomake inbound calls for service at similar times. A large volume ofinbound calls tends to lead to longer wait times during popular callingperiods resulting in customer dissatisfaction. As a consequence, duringperiods of heavy volumes and long hold times, a greater number ofinbound callers hang up or “silently” close their accounts by seekingother service providers with better service. Another example ofexcessive hold times affecting the behavior of inbound callers occurswith telemarketing. The volume of inbound calls in a marketing operationtends to increase dramatically shortly after a television advertisementis aired. Extended hold times result in a greater number of customerhang-ups and lost sales.

SUMMARY OF THE INVENTION

Therefore a need has arisen for a method and system which orders inboundinquiries, such as telephone calls, to improve the efficiency ofresponding to the inbound inquiries.

A further need exists for a method and system that forecasts thebehavior of those making inbound inquiries, such as inbound telephonecallers, to predict the outcome of an inbound inquiry.

A further need exists for a method and system that applies theforecasted behavior of those making inbound inquiries, such as inboundtelephone callers, to order the inbound inquiries for response byagents.

A further need exists for a method and system that solves for an optimumordering sequence for responding to inbound inquiries.

In accordance with the present invention, a method and system forordering inbound inquiries is provided that substantially eliminates orreduces disadvantages and problems associated with previously developedmethods and systems for responding to inbound inquiries. Inbound inquiryinformation associated with each inbound inquiry is applied to a modelto determine a priority value for ordering the inbound inquiry forresponse relative to other inbound inquiries.

More specifically, inbound inquiries may include inbound telephonecalls, e-mails, instant messages, or other electronic messages formats,such as those available through the internet. In an embodiment forscheduling inbound telephone calls, a telephone call receiving devicereceives plural inbound telephone calls for distribution to one or moreagents. The telephone call receiving device may include an ACD, a VRU, aPBX, a VOIP server or any combination of such devices that are operableto receive plural inbound telephone calls and redirect the inboundtelephone calls to one or more agents. The inbound telephone calls haveassociated caller information, such as ANI or DNIS information, whichthe receiving device interprets. ANI information identifies thetelephone number from which the inbound call originates, and DNISinformation identifies the telephone number to which the inbound callwas directed.

A scheduling module interfaced with or integrated within the receivingdevice determines an order for the handling of inbound telephone callsbased in part on the predicted outcome of the inbound telephone calls.In one embodiment, the scheduling module places the inbound calls in aqueue, the queue acting as a virtual hold, and applies a caller model tothe caller information associated with the inbound calls in order toforecast the predicted outcome of the inbound calls. The order forhandling the inbound calls is based on a priority value calculated fromthe application of a caller model to the caller information by a callevaluation sub-module and based on the capacity of the receiving device.As calls are scheduled by the scheduling module for handling by thereceiving device, the scheduling module releases the inbound calls fromthe virtual hold queue and places the inbound calls in the queue of thereceiving device. In an alternative embodiment, the scheduling module orthe receiving device may perform real-time scheduling of inbound callinventory by re-ordering queues of the receiving device based on thepriority value.

The call evaluation sub-module uses algorithms and models provided by amodeling module that analyzes inbound call histories to forecastoutcomes of pending inbound calls. It utilizes the forecasts to computepriority values. For example, in the modeling module, performinglogistic regression on prior inbound calls using caller and/or callinformation and prior call history as independent (or predictive)variables and a dependent variable of caller attrition, provides a modelthat forecasts pending inbound caller attrition based on the callerand/or call information. Alternatively, performing linear regressionmodeling on prior inbound calls, using caller and/or call information asindependent (or predictive) variables and a dependent variable ofconnect time, provides a model that forecasts the expected agent talktime for each incoming call.

Predictive variables for the logistic and linear regression equationsmay include call information such as the originating number or exchange,the originating location, the dialed number, the time of day and thelikely purpose of the call. In addition, they may include callerinformation such as account information derived from association of theoriginating number and an account data base, or derived from data inputby the inbound caller by a VRU. From caller information and/or callinformation, additional predictive variables are available forforecasting the outcome of the inbound call, including demographicinformation that may be associated with the call and/or caller.

In one embodiment, the call evaluation sub-module estimates one or morequantities of interest with one or more models provided by the modelingmodule, and computes the call's priority value based on the quantitiesof interest. For example, the call value of “the probability of a saleper minute of expected talk time” may be estimated by dividing theestimated probability of a sale by the estimated talk time.

In another embodiment, the call evaluation sub-module uses the estimatedquantities of interest to formulate and solve a constrained optimizationproblem based on conventional mathematical techniques, such as thesimplex method for linear problems or the Conjugate gradient andProjected Lagrangian techniques for Non-linear problems. For example,call evaluation sub-module may present a value that represents thesolution to maximizing objectives such as agent productivity to eitherminimize attrition or to produce product sales.

The present invention provides a number of important technicaladvantages. One important technical advantage is that inbound inquiries,such as inbound telephone calls, are ordered for response based at leastin part on the predicted outcome of the inbound inquiries. This allows,for instance, agents to respond to customers that are more sensitive toholding time before responding to customers who are less sensitive toholding time. This also allows, as another example, enhanced efficiencyof handling of inbound telephone calls by seeking to improve the overalloutcomes of the inbound calls based on the forecasted outcomes. Forinstance, in a telemarketing environment, inbound callers with a higherlikelihood of purchasing an item or service may be responded to beforecustomers with a lower probability of a purchase outcome. In fact,computing estimated outcomes and then formulating and solving theappropriate constrained optimization problem provides an orderingsequence that maximizes purchases made by inbound callers responding toa television advertisement.

Another important technical advantage of the present invention is thatforecasted outcomes are available with minimal caller information.Generally the identity and purpose of inbound calls are difficult todiscern because little information is available regarding the inboundcaller. The use of statistical analysis of historical inbound callingdata allows accurate modeling of outcomes with minimal knowledge of theidentity and purpose of the inbound caller.

Another important technical advantage of the present invention is thatinbound calls are prioritized based on caller and call information. Thepresent invention allows flexible use in a number of inbound inquiryenvironments such as telemarketing and customer service environments.Caller models may have different predictive variables depending upon themodeled outcome and the caller information obtained with the inboundinquiry. For instance, telemarketing applications using models thatforecast probability of a purchase may focus on predictive variablesderived from demographic information based on the origination of theinbound call. In contrast, customer service applications using modelsthat forecast caller attrition may have more detailed predictivevariables derived from customer account information. Thus, inboundcalling models and objectives may be closely tailored to a user'sparticular application. Also, estimates of the inbound call talk timemay lead to constrained optimization solutions designed to maximize theuse of the available agent talk time. Further, an overall responsestrategy that accounts for electronic message inquiries as well astelephone inquiries is more easily adopted.

BRIEF DESCRIPTION OF THE DRAWINGS

A more complete understanding of the present invention and advantagesthereof may be acquired by referring to the following description takenin conjunction with the accompanying drawings, in which like referencenumbers indicate like features, and wherein:

FIG. 1 depicts a block diagram of an inbound telephone call receivingdevice interfaced with an inbound scheduling system; and

FIG. 2 depicts a flow diagram of a method for ordering inbound callersfor response by agents.

DETAILED DESCRIPTION OF THE INVENTION

Preferred embodiments of the present invention are illustrated in theFIGURES, like numeral being used to refer to like and correspondingparts of the various drawings.

Under normal circumstances, inbound telephone calling centers maintainholding times for inbound callers within desired constraints byadjusting the response capacity of the calling center. For instance,during projected or actual periods of heavy inbound calling volume,additional agents may be assigned to respond to inbound calls by addingagents to the calling center or by reducing the number of outboundcalls. However, once the overall capacity of a calling center isreached, inbound calls in excess of calling center capacity willgenerally result in increased holding times for the inbound callers.

Inadequate capacity to handle inbound calls may result from periodicincreases in the number of inbound calls during popular calling times,or may result from one time surges due to factors such as system-widecustomer service glitches or the effects of advertising. Generally, theexcess inbound calls are assigned to hold for an available agent inqueues of an inbound telephone call receiving device and are handled ona first-in first-out basis for each holding queue. Often, the result ofexcessive hold times is that customers having a greater sensitivity tolong hold times will hang-up in frustration.

Responding to holding inbound callers on a first-in-first-out basis doesnot necessarily provide the most efficient results for a calling center.Agent time is used most efficiently when an agent is responding toinbound callers most likely to achieve a desired outcome. For instance,in a telemarketing role an agent is most productive when speaking withinbound callers likely to purchase the marketed service or product.Similarly, in a customer service role, an agent is most productive whenspeaking with inbound callers who provide a greater rate ofprofitability to the calling center. Thus, routing calls to agents on afirst-in-first-out basis does not provide the most efficient use ofagent time when inbound callers having a higher probability of a desiredoutcome are treated in the same manner as inbound callers having a lowerprobability of a desired outcome. The same principle applies wheninbound inquiries are received in alternative formats, such as e-mail orinstant messages.

Referring now to FIG. 1, a block diagram depicts an inbound schedulingsystem 10 that schedules inbound telephone calls for response by agentsin an order based in part on the predicted outcome of the inboundtelephone calls. Inbound scheduling system 10 includes a schedulingmodule 12, a call evaluation sub-module 13, and a modeling module 14,and is interfaced with an inbound call history data base 16 and accountinformation data base 18. Modeling module 14 builds one or more modelsthat forecast the outcomes of inbound calls using inbound call historyfrom data base 16 and/or from account information of data base 18.Scheduling module 12 applies the models to forecast outcomes of pendinginbound calls and schedules an order for agents to respond to thepending inbound calls based on the call evaluation sub-module 13.Modeling module 14 builds statistical models and call evaluationsub-module 13 computes the priority value which is used by schedulingmodule 12. The priority value is the result of computations based on themodels, but also of solutions to optimization problems that may bedefined on computations based on the models.

Inbound scheduling system 10 interfaces with an inbound telephone callreceiving device 20. Scheduling system 10 and receiving device 20 may beintegrated in a single computing platform, or may be based on separatecomputing platforms interfaced with proprietary application programminginterfaces of the receiving device 20 or interfaced with commerciallyavailable application middle ware such as Dialogic's CT Connect orMicrosoft's TAPI. Inbound telephone call receiving device 20 is aconventional telephony device that accepts inbound telephone callsthrough a telephony interface 22, such as conventional T1 or fiberinterfaces. Inbound telephone call receiving device 20 may include anACD, a VRU, a PBX, a VOIP server or any combination of such conventionaldevices. Inbound telephone calls received through interface 22 aredistributed to one or more answering queues 24 for response by agentsoperating telephony devices 26. Although FIG. 1 depicts an embodiment ofthe present invention that orders inbound telephone calls, alternativeembodiments apply scheduling module 12 and modeling module 14 toschedule other types of inbound inquiries, such as e-mail or instantmessage inquiries, by interfacing inbound scheduling system 10 with anappropriate inbound receiving device, such as an internet server.

Inbound telephone call receiving device 20 accepts inbound telephonecalls through interface 22 and obtains caller information associatedwith the inbound calls such as ANI and DNIS information. When receivingdevice 20 includes a VRU, additional caller information, such as accountinformation, is obtained through automated interaction with the inboundcallers. For instance, a VRU may query an inbound caller to provide anaccount number or a reason for the call, such as to open a new account,to change account information, to check account information, to purchasea particular service or item, or to collect inbound caller informationwhen ANI is not operative, such as when caller-ID is blocked. In analternative embodiment, inbound inquiries may include e-mail or instantmessages that provide inquiry information based on login ID, e-mailaddress, IP or instant message address. In such an embodiment,additional information can be gathered by an automated e-mail or instantmessage survey response that requests a phone number, purchase interest,account number or other relevant information.

Receiving device 20 passes the caller information to scheduling system10, such as through a data query, and awaits a response from schedulingsystem 10 before allocating the inbound call to an answering queue. Inaddition, receiving device 20 provides scheduling system 10 with agentactivity and capacity. For instance, a receiving device 20 may includeboth a VRU and an ACD with the ACD providing agent activity information.When receiving device 20 includes a VRU, an “out of order” response maybe provided by scheduling system 10 when operator capacity isunavailable or in high use, meaning that the first call in is notnecessarily the first call out.

Scheduling module 12 keeps inbound calls in a queue that acts as avirtual hold until a response is desired and then releases the inboundcall for placement in an answering queue 24. Thus, scheduling system 10responds to queries from receiving device 20 based on the priority ofthe inbound call, essentially creating an ordered queue on receivingdevice 20 by delaying the response to inbound calls having lowerpriorities. In one alternative embodiment, scheduling module 12 mayre-order queues directly within receiving device 20 to allow real-timeordering of inbound telephone call queues.

Scheduling module 12 obtains data to apply to a caller model byperforming a look-up based on the caller information received fromreceiving device 20. Caller information may include account number, zipcode, area code, telephone exchange, reservation number or otherpertinent information obtained from the inbound caller, such as with aVRU, or derived from information obtained by the receiving device 20with the inbound call, such as ANI or DNIS information. The nature ofcaller information depends upon the implementation of scheduling system10 and is generally configurable through a graphical user interfaceprovided with conventional receiving devices. In addition to the callerinformation, scheduling module 12 may query and join data from othersources such as zip+4 and credit bureau sources and demographicinformation otherwise derivable from the caller information.

When sufficient capacity exists for response by receiving device 20,scheduling system 10 releases calls immediately back to receiving device20. In other words inbound calls are not delayed if sufficient capacityexists to handle the inbound calls, but are routed for immediateanswering. When capacity is tight on receiving device 20, calls aredelayed on a virtual hold by scheduling system 10 until an appropriatetime based on the priority value computed by the call evaluationsub-module 13. Whether or not inbound calls are delayed, schedulingsystem 10 gathers and stores data for the inbound calls in the inboundcall history data base 16. The outcome of inbound calls is also gatheredand stored along with forecasted outcomes to provide a detailedcall-by-call history for use in future modeling and for verification offorecasted outcome versus actual outcome. For instance, once an inboundcall is completed, results such as a successful connect with an agent,an abandoned call, a purchase, or customer attrition from billingrecords are associated with inbound calls.

Modeling module 14 creates caller models by performing statisticalanalysis on appropriate data taken from inbound call history data base16 and account information data base 18. The statistical analysisperformed by modeling module 14 builds models by associating the outcomeof a call (i.e., the dependent variable) to the information availablewhen the call is received (i.e., the independent variables) The endresult of each model is equations that when computed provide a forecastfor the outcome of interest (e.g., agent talk time, sale: yes/no,account cancelled within x days: yes/no). The application of callermodels to caller and/or call information may be performed as callsarrive, or may be performed preemptively to calculate potential scoresin the beginning of a time period to provide more rapid response whencircumstances warrant.

One type of statistical analysis appropriate for modeling discreteoutcomes (e.g., sale: yes/no, account cancelled within x days: yes/no)is logistic regression. Some examples of forecasted outcomes includeestimating probability an inbound caller will hang up in a predeterminedhold time, the probability a customer will cancel an account, or theprobability the customer will make a purchase. As an example, thefollowing logistic regression equation forecasts the probability ofpurchase based on the independent variables income and age:exp(a ₀ +a ₁*age+a ₂*income)/[1+exp(a ₀ +a ₁*age+a ₂*income)]

-   -   where:    -   a₀=a constant representing the model's intercept    -   a₁=the parameter for the predictive variable age    -   a₂=the parameter for the predictive variable income

Another type of statistical analysis appropriate for modeling continuousoutcomes, such as talk time or sale amount, is linear regression. Forexample, the following linear regression equation forecasts agent talktime (“TT”) based on independent variables time-on-books (“TOB”),time-of-day between 8–9 am (“TOD”), balance (“BAL”) and delinquencylevel (“DL”):TT=b ₀ +b ₁ TOB+b ₂ TODflag+b ₃ BAL+b ₄ DL

-   -   b₀=a constant representing the model's intercept    -   b₁=the parameter for the predictive variable TOB    -   b₂=the parameter for the predictive variable TOD        -   (i.e., Was the call between 8–9 (1=yes, 2=no))    -   b₃=the parameter for the predictive variable BAL    -   b₄=the parameter for the predictive variable DL

In alternative embodiments, statistical models that forecast outcomesmay be developed by a number of alternative techniques. For instance,neural networks, classification and regression trees (CART), and Chisquared automatic detection (CHAID) are statistical techniques formodeling both discrete and continuous dependent variables. Anotherexample is cluster analysis, which, with an association of the resultingcluster assignment equations to the dependent variables allows forsimplified models or may be used to improve the effectiveness of othertechniques. Each alternative statistical technique will result indifferent forecasting equations which may have advantages for differenttypes of forecasting circumstances. Essentially, however, each type ofequation will associate an outcome as a dependent variable with the calland caller information available while the call is processed asindependent variables. In general mathematical terms, for each possiblediscrete outcome, such as sale: yes/no, account cancelled within x days:yes/no, where i=1, . . . M:Prob(outcome=i)=f _(i)(x(1), x(2), . . . x(N))

-   -   where:    -   x(i) stands for the ith independent variable, and    -   f_(i)(x(1), x(2), . . . x(N)) stands for the modeling equation        for outcome i and can take different forms depending upon the        statistical technique chosen

For each continuous outcome, such as talk-time or amount of sale:Estimate of dependent variable=g(x(1), x(2), . . . x(N))

-   -   where:    -   x(i) stands for the ith independent variable, and    -   g(x(1), x(2), . . . x(N)) stands for the modeling equation, and        can take different forms depending upon the statistical        technique chosen.

Forecasted outcomes and predictive variables are user defined, anddepend on the inbound inquiries being scheduled. As an example, forinbound inquiries related to a solicitation effort, such as telephonecalls following a TV advertisement, the outcome may be: yes/no/hang-up;amount of purchase (continuous); amount by type of product (continuous)split by product type; approval of a credit application yes/no. Asanother example, for customer service inquiries, exemplary outcomes maybe: customer satisfaction yes/no; closure of account within x daysyes/no; change in loan balance within x days (continuous); or disputewith a positive resolution/dispute with a negative resolution/nodispute. Other types of outcomes that may be of interest to bothpost-solicitation and customer service inquiries include: agenttalk-time (continuous); agent talk time by type of agent (continuoussplit by agent type, such as general/supervisor/specialist).

The selection of predictive variables depends upon the type of dataavailable and the circumstances of the outcome which is beingforecasted. For example, in a situation in which the inquiries come fromindividuals known to the calling center, data available for predictingoutcomes may include: account information; application information, suchas employment, age, income, bank account information; relationship datasuch as other account information; results of other modeling efforts,such as behavior and response scores; credit bureau data; check clearingdata; e-mail domain information; and trigger events, such assolicitations, TV advertisements, and account statements. Whengeographic location of the call or caller can be established, this mayyield additional predictive data, such as zip+4 credit bureauinformation, census demographics, and third party models, such as creditbureau clusters. Data available from a call itself may includeinformation input through a VRU, including branch sequence and initialnumber called, and the time at the place of the origination of theinbound inquiry. In addition, the call environment itself may providedata based on the types and number of calls received in a recent periodof time, the type and number within a period of time, such as aparticular hour or day, and the results provided by the calls.

Once the modeling equations are applied and outcomes such as probabilityof purchase or expected talk time are estimated, the call evaluationsub-module computes the priority value. In one embodiment of theinvention, the priority value of a call might be the estimatedprobability of a purchase. Inbound calls having higher probabilities ofpurchase may be answered first. In another embodiment, the priorityvalue of a call might be given by dividing the estimated probability ofpurchase by the expected talk time of the call. The most productivecalls are given are given a greater priority value for response by anagent. In this way, agent productivity is implicitly improved since agreater portion of the agent's time is spent talking with potentialcustomers having a higher probability of making a purchase.

In another embodiment of the invention, scheduling module 12 ordersinbound inquiries to explicitly optimize a desired outcome, such as amaximum number of purchases or a minimum number or losses due toattrition, taking into account the limitations of the environmentoperating at the time. Quantities of interest, such as probability of asale, probability of attrition, or expected talk time, are estimatedwith models generated by modeling module 14. The estimated quantities ofinterest are used to solve a constrained optimization problem withconventional mathematical techniques, such as the simplex method forlinear problems or the Conjugate gradient and Projected Lagrangiantechniques for Non-linear problems.

One example of optimization applied to inbound telephone calls is themaximization of agent productivity to minimize attrition of inboundcallers, as illustrated by the following equation:Max sum x(i)*(p₂(i)−p₁(i))

-   -   i=1, . . . N

Subject to:sum x(i)*t(i)=<T

-   -   i=1, . . . N        x(i) in (0,1)    -   where:    -   x(i) (the decision variable) denotes whether call i should be        kept or dropped    -   p₁(i) is the estimate for the probability of attrition for the        caller's account if the call is not answered    -   P₂(i) is the estimate for the probability of attrition for the        caller's account if the call is answered    -   t(i) is the estimate of the expected talk-time for call i    -   T is the total available Agent time for a user-defined time        interval    -   N is the number of calls in queue

Once the constrained optimization problem is solved, letting Q be theoptimal dual variable for the talk-time constraint, the call priorityvalue may be given by the reduced objective value: P₂(i)−P₁(i)−Q*t(i).

Another example of optimization applied to inbound telephone calls isthe maximization of agent productivity to produce sales to inboundcallers, as illustrated by the following equation:Max sum x(i)*q(i)

-   -   i=1, . . . N

Subject to:sum x(i)*t(i)=<T

-   -   i=1, . . . N        x(i) in (0,1)    -   where:    -   x(i) (the decision variable) denotes whether call i should be        kept or dropped    -   q(i) is the estimate for the probability that the call will        result in a sale    -   t(i) is the estimate of the expected talk-time for call i    -   T is the total available Agent time for a user-defined time        interval    -   N is the number of calls in queue.

Once the constrained optimization problem is solved, letting R be theoptimal dual variable for the talk time constraint, the call priorityvalue may be given by the reduced objective value: q(i)−R*t(i).

Although FIG. 1 depicts an embodiment of the present invention thatorders inbound telephone calls, alternative embodiments apply schedulingmodule 12 and modeling module 14 to schedule other types of inboundinquiries, such as e-mail or instant message inquiries, by interfacinginbound scheduling system 10 with an appropriate inbound receivingdevice, such as an internet server. The scheduling module may bereceiving inbound inquiries from a plurality of sources (e.g. ACD, VRU,internet server) and returning priority values to unified or separatepools of agents.

Referring now to FIG. 2, a flow diagram depicts a process for schedulinginbound calls for response by an agent. The process begins at step 30with the building of models from inbound call history. The inbound callhistory used to model the outcomes of interest may be a sample drawnfrom historical inbound calls of the same nature as the outcomes to bemodeled or may be specifically designed during a test phase. Forinstance, a television advertisement aired in a single or limited numberof television markets representative of the total targeted audience maybe used to generate inbound calls having a volume within the capacityconstraints of the calling center. The outcome of the inbound calls fromthe sample advertisement may then be used to create a model specific tothe nature of the product sold by the advertisement. Theadvertisement-specific model is then used for the time periods duringwhich the advertisement is presented to wider audiences so that inboundcalls having a greater probability of resulting in a purchase will havea higher priority for response by an agent.

At step 32, inbound calls are received by the receiving device.Generally, inbound calls arrive continuously at the receiving device atrates that vary over time. The receiving device answers the inboundcalls in a conventional manner and, at step 34, determines call and/orcaller information. Call and/or caller information is determined throughanalysis of ANI or DNIS information that arrives with inbound calls andalso through data gathering such as by interaction with a VRU.

At step 36, call and/or caller information is provided to the schedulingmodule for a determination of a priority value based on the forecastedoutcome of the inbound call. At step 38, the scheduling moduledetermines if additional information is needed for calculation of theoutcome forecast. For instance, account information may be acquired bythe receiving device and passed to the scheduling module, or thescheduling module can acquire all or part of the information. Ifadditional information is needed, at step 40, caller information is usedto obtain additional account or demographic information. At step 42, thecaller model is applied to caller information, account informationand/or demographic information to determine a priority value for theinbound call. At step 43, in one embodiment, the receiving device sortsqueues according to the priority value, reducing or eliminating the needfor a virtual hold by the release of calls from the scheduling module.For instance, a linked list for receiving devices that support linedlist data structures may be used to aid in the scheduling of inboundcalls.

At step 44, inbound calls are scheduled for response by an agentinterfaced with the receiving device. Inbound calls having lowerpriority values are placed on virtual hold while inbound calls havinghigher priority values are returned to the receiving device and placedin a queue for response by an agent. The length of a virtual hold for aninbound call depends upon the volume of inbound calls, the capacity ofthe receiving device, the talk time of the agents per call and thepriority value of an inbound call relative to other pending inboundcalls. Based on these factors, an inbound call is placed in virtual holdtime and is forwarded to the receiving device in priority value orderwhen agent resources are available and/or when a maximize hold timeparameter has been exceeded. Alternatively, in embodiments in which thereceiving device can sort or change the order of an inbound queue basedon available data including the priority value, the inbound queues ofthe receiving device may be re-ordered on a real-time basis asadditional inquiries are received.

At step 46, the outcome of inbound calls is stored in the inbound callhistory data base. The inbound history data base tracks factors such ascall success or abandonment and ultimate call outcome. Call outcome mayinclude directly quantifiable factors such as a purchase decision orless quantifiable factors such as customer satisfaction as reflected byaccount usage, cancellations and related information that is derivablefrom account databases and other sources.

One example of an application of the inbound scheduling system is acredit card service calling center. Customers tend to make inbound callsat similar times of the day which leads to longer hold times wheninbound call volumes are high. Often, inbound callers hang up or simplyjust “silently” close their account when hold times are excessive forthat caller. Other customers are less sensitive to hold times and thusless likely to alter their purchasing habits or account status as afactor of hold times. The scheduling system enhances the overall benefitfrom inbound telephone calls by providing a higher priority to inboundcalls that are forecasted to have a desired result, such as increasedaccount usage. Further, the effectiveness may be tested withchampion/challenger testing that compares results of subsets of inboundcalls in which one segment is prioritized and the other segment is notprioritized or is prioritized with a different priority strategy.

Another example of the present invention is an application for anintegrated response center that simultaneously accepts inquiries fromdifferent types of communication media, such as simultaneous inquiresfrom telephone calls, VOIP, e-mails and instant messages. In such anenvironment, agent response to inquiries may be via the same media asthe inquiry or through cross-channel communication. For instance, ane-mail inquiry may result in an e-mail response or, alternatively, in atelephone call response. Further, the priority of the response maydepend, in part, on the media of the inquiry. For instance, generally ane-mail inquiry will have a lower priority than a telephone inquiry sincea customer generally will not expect as rapid of a response when thecustomer sends an e-mail inquiry. However, if the customer who sent thee-mail inquiry has a high probability of purchase, an immediate responseby a telephone call might provide a better sales outcome for an agent'stime, even if a telephone inquiry with a customer having a lowprobability of purchase is left on hold while the agent places anoutbound call.

In a highly constrained resource environment, particularly low priorityinquiries, such as inquiries with a low probability of purchase, may bescheduled for outbound attempts at a later time in order to preserveresponse resources for higher priority inquiries. For instance, a lowpriority inbound telephone caller may be given a voice message thatinforms the caller of an excess wait time and that he will be contactedat a future time. The future time is determined by the caller's prioritycompared with the actual and projected priority of other inboundinquiries and the capacity of the agents to respond to the inquires.Thus, if the capacity of the available agents is projected to exceedinbound inquiry demand and higher priority inquiry backlog in two hours,the low priority inbound caller may be given a message to expect a callin two hours. Similarly, an automated e-mail message may be provided toan e-mail inquiry informing the e-mail inquirer that he may expect aresponse at a specific time. In this way, inquiries are scheduled foroutbound contact attempts on a prioritized basis rather than on afirst-in-first-out basis. In one alternative embodiment, the inquirermay be prompted for the best time and communication channel, and anoutbound contact attempt will be attempted at that time.

Although the present invention has been described in detail, it shouldbe understood that various changes, substitutions and alterations can bemade hereto without departing from the spirit and scope of the inventionas defined by the appended claims.

1. A method for ordering inbound inquiries, the method comprising:receiving plural inbound inquiries, each inbound inquiry havingassociated inquiry information; applying a model to the inquiryinformation to determine a priority value for each inquiry, the modelestimating the probability of an outcome of an inbound inquiry having apredetermined result; and ordering the inbound inquiries with thepriority values.
 2. The method of claim 1 wherein the method inquiriescomprise e-mail messages.
 3. The method of claim 1 wherein the methodinquiries comprise instant messages.
 4. The method of claim 1 whereinthe inbound inquiries comprise inbound telephone calls having associatedcaller information.
 5. The method of claim 4 wherein the callerinformation comprises automatic number identification information. 6.The method of claim 4 wherein the caller information comprisedestination number identification information.
 7. The method of claim 4further comprising: gathering the caller information with a voiceresponse unit.
 8. The method of claim 4 further comprising: associatingdemographic information with each inbound telephone call based on thecaller information of the inbound call; and applying the model to thecaller information to determine the priority value for each telephonecall.
 9. The method of claim 4 wherein the model predicts callerbehavior.
 10. The method of claim 9 wherein the priority value comprisesa probability that the telephone call will result in a purchase.
 11. Themethod of claim 9 wherein the priority value comprises a probabilitythat the caller associated with the telephone call will terminate thecall after a hold time.
 12. The method of claim 1 further comprising:developing plural models from a history of inbound inquiries to forecastplural outcomes that determine the priority value.
 13. The method ofclaim 12 wherein developing the model further comprises: applyingregression analysis to the history to calculate the priority value. 14.The method of claim 12 further comprising: determining the outcomes ofthe plural inbound inquiries; and updating the history with the outcomesof the plural inbound inquiries.
 15. The method of claim 12 whereindeveloping the caller model further comprises: updating the model withthe updated history.
 16. A method for determining inbound telephone callpriority, the method comprising: developing one or more models from ahistory of inbound calls, the history having caller information andoutcome results from inbound telephone calls; applying the model tocaller information of a pending inbound call to predict an outcome ofthe pending inbound call; and associating a priority with the pendinginbound call, the priority based on the predicted outcome.
 17. Themethod of claim 16 wherein the caller information comprises telephonyinformation received with the pending inbound call.
 18. The method ofclaim 17 wherein the telephony information comprises automatic numberidentification information.
 19. The method of claim 17 wherein thetelephony information comprises destination number identificationinformation.
 20. The method of claim 17 wherein the caller informationfurther comprises account information, the method further comprising:obtaining account information for the pending inbound call, the accountinformation stored in a database by association with the telephonyinformation.
 21. The method of claim 17 wherein the telephonyinformation further comprises information input by the caller through avoice response unit.
 22. The method of claim 21 further comprising:obtaining account information for the pending inbound call based on thetelephony information.
 23. The method of claim 16 wherein developing amodel further comprises: using the caller information as predictivevariables that model outcome results.
 24. The method of claim 23 whereinthe model comprises a logistic regression model.
 25. The method of claim23 wherein the model comprises a linear regression model.
 26. The methodof claim 16 further comprising: placing the pending inbound call in thequeue of an automatic call distribution system in an order based on thepriority of the pending inbound call.
 27. The method of claim 26 whereinthe predicted outcome comprises a purchase resulting from the pendinginbound call.
 28. The method of claim 26 wherein the predicted outcomecomprises the hold time of the pending inbound call.
 29. The method ofclaim 16 wherein associating a priority further comprises optimizing theorder for the inbound telephone calls.
 30. The method of claim 29wherein optimizing the order comprises solving a constrainedoptimization problem using one or estimates from one or more models. 31.The method of claim 29 wherein optimizing further comprises maximizingagent productivity to minimize caller attrition.
 32. The method of claim29 wherein optimizing further comprises maximizing agent productivity toproduce sales.
 33. A system for scheduling inbound calls, the systemcomprising: a receiving device operable to receive plural inboundinquiries and to provide the inbound inquiries to one or more agents;and a scheduling module interfaced with the receiving device, thescheduling module operable to order the inbound inquiries for handlingby the receiving device, the order based in part on the predictedoutcome of the inbound inquiries.
 34. The system of claim 33 wherein theinbound inquiries comprise inbound telephone calls.
 35. The system ofclaim 33 wherein the receiving device comprises an automatic calldistribution system.
 36. The system of claim 33 wherein the receivingdevice comprises a server that supports voice over internet protocol.37. The system of claim 33 wherein the receiving device comprises avoice response unit.
 38. The system of claim 34 further comprising: aninbound call history data base operable to store outcome results andcaller information from plural completed inbound calls; and a modelingmodule interfaced with the history database and operable to modelinbound call outcomes from the stored outcome results and callerinformation.
 39. A system for responding to inbound calls, the systemcomprising: a telephone call receiving device interfaced with a networkto receive plural inbound calls; and a scheduling system associated withthe receiving device and having a scheduling module that prioritizes theinbound calls in accordance with forecasted outcomes for the inboundcalls; wherein the scheduling system places one or more inbound calls onhold and then releases the inbound call from hold based on the priorityof the inbound call.
 40. The system of claim 39 wherein the telephonecall receiving device comprises an automatic call distribution systemthat incorporates the scheduling system.
 41. The system of claim 39wherein the scheduling system forecasts outcomes with a model derivedfrom a history of inbound calls.
 42. The system of claim 39 wherein thescheduling system orders the inbound calls to optimize an objectivefunction.
 43. The system of claim 42 wherein the objective functioncomprises agent productivity to minimize inbound call attrition.